158 research outputs found

    Consistent patterns of common species across tropical tree communities

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    International audienceAbstract Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1–6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7 , we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

    A Importância da Atenção Primária na Prevenção e Detecção Precoce do Câncer de mama

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    OBJECTIVE: To describe the importance of primary care in the prevention and early detection of breast cancer. METHOD: It consists of an integrative review, carried out based on the following guiding question: How important is primary care in the prevention and detection of breast cancer? using the PICO strategy, where “p” population: women receiving primary health care, “I” interest: The importance of primary care in detecting breast cancer in women, and “C” and “O” context: Impacts of breast cancer on women and how primary care prevention and detection can reduce them. The filter used for the searches was with the descriptors: “Primary health care”; “Breast neoplasms”; “Disease prevention”, using the Boolean operator “AND” and “OR”. RESULTS: The final sample consisted of 6 articles, which resulted in 2 categories: Perception of health professionals in primary care regarding the detection and prevention of breast cancer; Breast cancer prevention. CONCLUSION: It is understood that the support of the health professional is of great importance during care for women, comprehensive support must be offered to women, welcoming them in Primary Care, resolving all their doubts about the signs and symptoms of breast cancer, raising awareness about the importance of knowing your body.OBJETIVO: Descrever a importância da atenção primária na prevenção e detecção precoce do câncer de mama. MÉTODO: Consiste numa revisão integrativa, realizada com base na seguinte pergunta norteadora: Qual a importância da atenção primária na prevenção e detecção do câncer de mama? sendo utilizado a estratégia PICO, em que “p” população: mulheres atendidas na atenção primária a saúde, “I” interesse: A importância da atenção primária na detecção do câncer de mama em mulheres, e “C” e “O” contexto: Impactos do câncer de mama em mulheres e como a prevenção e detecção da atenção primária podem diminuí-los. O filtro utilizado para as buscas foi com os descritores: “Atenção Primária à saúde”; “Neoplasias da mama”; “Prevenção de doenças”, utilizando o operador booleano “AND” e “OR”.  RESULTADOS: A amostra final foi constituída de 6 artigos, que resultaram em 2 categorias: Percepção de profissionais de saúde na atenção primária acerca da detecção e prevenção do câncer de mama; Prevenção do câncer de mama. CONCLUSÃO: Entende-se que, o apoio do profissional de saúde é de grande importância durante o atendimento à mulher, deve-se oferecer um suporte integral a mulher, acolhê-la na Atenção Básica sanando todas as suas dúvidas sobre os sinais e sintomas do câncer de mama, conscientizando-a sobre a importância de conhecer seu corpo

    Consistent patterns of common species across tropical tree communities

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    Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

    Mapping density, diversity and species-richness of the Amazon tree flora

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    Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

    Table_1_Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit.docx

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    ObjectivesTo assess the ABC2-SPH score in predicting COVID-19 in-hospital mortality, during intensive care unit (ICU) admission, and to compare its performance with other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score).Materials and methodsConsecutive patients (≥ 18 years) with laboratory-confirmed COVID-19 admitted to ICUs of 25 hospitals, located in 17 Brazilian cities, from October 2020 to March 2022, were included. Overall performance of the scores was evaluated using the Brier score. ABC2-SPH was used as the reference score, and comparisons between ABC2-SPH and the other scores were performed by using the Bonferroni method of correction. The primary outcome was in-hospital mortality.ResultsABC2-SPH had an area under the curve of 0.716 (95% CI 0.693–0.738), significantly higher than CURB-65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Mortality Score, and the novel severity score.ConclusionABC2-SPH was superior to other risk scores, but it still did not demonstrate an excellent predictive ability for mortality in critically ill COVID-19 patients. Our results indicate the need to develop a new score, for this subset of patients.</p

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Contaminação dos recursos hídricos por micropoluentes emergentes e os possíveis métodos de tratamento para sua remoção

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    A escassez dos recursos hídricos aliada ao aumento nos níveis de contaminação tem sido alvo de preocupação por toda a comunidade. Recentemente, foram detectados novos compostos poluidores, em concentrações que variam entre ng.L-1 e µ.L-1, denominados de Contaminantes Emergentes (CEs). Essas substâncias são potencialmente prejudiciais ao meio ambiente e à saúde humana, e dificilmente são removidas pelos tratamentos convencionais de água e esgoto. Assim, o estudo objetivou elaborar uma revisão narrativa sobre as principais rotas de entrada dos CEs no ambiente aquático, os efeitos causados pela presença desses poluentes na água, e apresentar soluções de tratamento para a remoção desses contaminantes micropoluentes. Os CEs são introduzidos na água, sobretudo, por meio de fontes antropogênicas (lixiviados de aterros sanitários e esgotos domésticos e industriais) e estão associados à feminilização de animais, doenças neurológicas, reprodutivas e imunológicas, redução da diversidade de microinvertebrados nos rios e extinção de aves. Entre os métodos de tratamento, apresentam destaque na remoção dos CEs da água: o carvão ativado, filtração por membrana, filtração em margem, wetlands, lodos ativados, além dos processos oxidativos avançados. Cada uma dessas técnicas demonstra vantagens e desvantagens, sendo necessário um estudo mais acurado sobre as características do local a ser implantado o tratamento, a fim de determinar a mais adequada àquele ambiente.The scarcity of water resources and the increase in the levels of pollution of it has been a target of concern for those who depend on waters with the minimum level of quality for their proper uses. Recently, with the advancement of technologies, new polluting compounds were detected, in low concentrations, varying between ng.L-1 and µ.L-1, called emerging micropollutants. Although they are present in aquatic matrices in trace concentrations, they are potentially harmful to the environment and human health. Due to their ineffective removal in conventional water and sewage treatment plants, several studies have been carried out to determine technologies capable of attenuating these new pollutants, such as activated carbon, membrane filtration, bank filtration, wetlands, activated sludge, and advanced oxidative processes, to avoid the negative impacts caused by these contaminants. Thus, the present study aimed to develop a bibliographic review on the main routes of entry of emerging micro-pollutants into the aquatic environment, the potential effects caused by the presence of these pollutants in the water, and to present possible treatment solutions for the removal of these compounds

    Mapping density, diversity and species-richness of the Amazon tree flora

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    Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

    Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology.

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    In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics
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